The Role of Deleterious Substitutions in Crop Genomes

Patterns of the Predicted Mutation Burden in 19,778 Domesticated Barley Accessions Conserved Ex Situ

Long-term conservation of more than 7 million plant germplasm accessions in 1750 genebanks worldwide is a challenging mission. The extent of deleterious mutations present in conserved germplasm and the genetic risk associated with accumulative mutations are largely unknown. This study took advantage of published barley genomic data to predict sample-wise mutation burdens for 19,778 domesticated barley (Hordeum vulgare L.) accessions conserved ex situ. It was found that the conserved germplasm harbored 407 deleterious mutations and 337 (or 82%) identified deleterious alleles were present in 20 (or 0.1%) or fewer barley accessions. Analysis of the predicted mutation burdens revealed significant differences in mutation burden for several groups of barley germplasm (landrace > cultivar (or higher burden estimate in landrace than in cultivar); winter barley > spring barley; six-rowed barley > two-rowed barley; and 1000-accession core collection > non-core germplasm). Significant differences in burden estimate were also found among seven major geographical regions. The sample-wise predicted mutation burdens were positively correlated with the estimates of sample average pairwise genetic difference. These findings are significant for barley germplasm management and utilization and for a better understanding of the genetic risk in conserved plant germplasm.

Conservation genomics provides insights into genetic resilience and adaptation of the endangered Chinese hazelnut, Corylus chinensis

Global climate change has increased concerns regarding biodiversity loss. However, many key conservation issues still required further research, including demographic history, deleterious mutation load, adaptive evolution, and putative introgression. Here we generated the first chromosome-level genome of the endangered Chinese hazelnut, Corylus chinensis, and compared the genomic signatures with its sympatric widespread C. kwechowensis-C. yunnanensis complex. We found large genome rearrangements across all Corylus species and identified species-specific expanded gene families that may be involved in adaptation. Population genomics revealed that both C. chinensis and the C. kwechowensis-C. yunnanensis complex had diverged into two genetic lineages, forming a consistent pattern of southwestern-northern differentiation. Population size of the narrow southwestern lineages of both species have decreased continuously since the late Miocene, whereas the widespread northern lineages have remained stable (C. chinensis) or have even recovered from population bottlenecks (C. kwechowensis-C. yunnanensis complex) during the Quaternary. Compared with C. kwechowensis-C. yunnanensis complex, C. chinensis showed significantly lower genomic diversity and higher inbreeding level. However, C. chinensis carried significantly fewer deleterious mutations than C. kwechowensis-C. yunnanensis complex, as more effective purging selection reduced the accumulation of homozygous variants. We also detected signals of positive selection and adaptive introgression in different lineages, which facilitated the accumulation of favorable variants and formation of local adaptation. Hence, both types of selection and exogenous introgression could have mitigated inbreeding and facilitated survival and persistence of C. chinensis. Overall, our study provides critical insights into lineage differentiation, local adaptation, and the potential for future recovery of endangered trees.

Porous borders at the wild-crop interface promote weed adaptation in Southeast Asia

High reproductive compatibility between crops and their wild relatives can provide benefits for crop breeding but also poses risks for agricultural weed evolution. Weedy rice is a feral relative of rice that infests paddies and causes severe crop losses worldwide. In regions of tropical Asia where the wild progenitor of rice occurs, weedy rice could be influenced by hybridization with the wild species. Genomic analysis of this phenomenon has been very limited. Here we use whole genome sequence analyses of 217 wild, weedy and cultivated rice samples to show that wild rice hybridization has contributed substantially to the evolution of Southeast Asian weedy rice, with some strains acquiring weed-adaptive traits through introgression from the wild progenitor. Our study highlights how adaptive introgression from wild species can contribute to agricultural weed evolution, and it provides a case study of parallel evolution of weediness in independently-evolved strains of a weedy crop relative.

Deleterious and Adaptive Mutations in Plant Germplasm Conserved Ex Situ

Conserving more than 7 million plant germplasm accessions in 1,750 genebanks worldwide raises the hope of securing the food supply for humanity for future generations. However, there is a genetic cost for such long-term germplasm conservation, which has been largely unaccounted for before. We investigated the extent and variation of deleterious and adaptive mutations in 490 individual plants representing barley, wheat, oat, soybean, maize, rapa, and sunflower collections in a seed genebank using RNA-Seq technology. These collections were found to have a range of deleterious mutations detected from 125 (maize) to 83,695 (oat) with a mean of 13,537 and of the averaged sample-wise mutation burden per deleterious locus from 0.069 to 0.357 with a mean of 0.200. Soybean and sunflower collections showed that accessions acquired earlier had increased mutation burdens. The germplasm with more years of storage in several collections carried more deleterious and fewer adaptive mutations. The samples with more cycles of germplasm regeneration revealed fewer deleterious and more adaptive mutations. These findings are significant for understanding mutational dynamics and genetic cost in conserved germplasm and have implications for long-term germplasm management and conservation.

Genomic signatures of bottleneck and founder effects in dingoes

Dingoes arrived in Australia during the mid-Holocene and are the top-order terrestrial predator on the continent. Although dingoes subsequently spread across the continent, the initial founding population(s) could have been small. We investigated this hypothesis by sequencing the whole genomes of three dingoes and also obtaining the genome data from nine additional dingoes and 56 canines, including wolves, village dogs and breed dogs, and examined the signatures of bottlenecks and founder effects. We found that the nucleotide diversity of dingoes was low, 36% less than highly inbred breed dogs and 3.3 times lower than wolves. The number of runs of homozygosity (RoH) segments in dingoes was 1.6-4.7 times higher than in other canines. While examining deleterious mutational load, we observed that dingoes carried elevated ratios of nonsynonymous-to-synonymous diversities, significantly higher numbers of homozygous deleterious Single Nucleotide Variants (SNVs), and increased numbers of loss of function SNVs, compared to breed dogs, village dogs, and wolves. Our findings can be explained by bottlenecks and founder effects during the establishment of dingoes in mainland Australia. These findings highlight the need for conservation-based management of dingoes and the need for wildlife managers to be cognisant of these findings when considering the use of lethal control measures across the landscape.

Unraveling Prevalence and Effects of Deleterious Mutations in Maize Elite Lines across Decades of Modern Breeding

Future breeding is likely to involve the detection and removal of deleterious alleles, which are mutations that negatively affect crop fitness. However, little is known about the prevalence of such mutations and their effects on phenotypic traits in the context of modern crop breeding. To address this, we examined the number and frequency of deleterious mutations in 350 elite maize inbred lines developed over the past few decades in China and the United States. Our findings reveal an accumulation of weakly deleterious mutations and a decrease in strongly deleterious mutations, indicating the dominant effects of genetic drift and purifying selection for the two types of mutations, respectively. We also discovered that slightly deleterious mutations, when at lower frequencies, were more likely to be heterozygous in the developed hybrids. This is consistent with complementation as a potential explanation for heterosis. Subsequently, we found that deleterious mutations accounted for more of the variation in phenotypic traits than nondeleterious mutations with matched minor allele frequencies, especially for traits related to leaf angle and flowering time. Moreover, we detected fewer deleterious mutations in the promoter and gene body regions of differentially expressed genes across breeding eras than in nondifferentially expressed genes. Overall, our results provide a comprehensive assessment of the prevalence and impact of deleterious mutations in modern maize breeding and establish a useful baseline for future maize improvement efforts.

Evolutionary dynamics and adaptive benefits of deleterious mutations in crop gene pools

Mutations with deleterious consequences in nature may be conditionally deleterious in crop plants. That is, while some genetic variants may reduce fitness under wild conditions and be subject to purifying selection, they can be under positive selection in domesticates. Such deleterious alleles can be plant breeding targets, particularly for complex traits. The difficulty of distinguishing favorable from unfavorable variants reduces the power of selection, while favorable trait variation and heterosis may be attributable to deleterious alleles. Here, we review the roles of deleterious mutations in crop breeding and discuss how they can be used as a new avenue for crop improvement with emerging genomic tools, including HapMaps and pangenome analysis, aiding the identification, removal, or exploitation of deleterious mutations.

Deleterious mutation load in the admixed mice population

Deleterious mutation loads are known to correlate negatively with effective population size (Ne). Due to this reason, previous studies observed a higher proportion of harmful mutations in small populations than that in large populations. However, the mutational load in an admixed population that derived from introgression between individuals from two populations with vastly different Ne is not known. We investigated this using the whole genome data from two subspecies of the mouse (Mus musculus castaneus and Mus musculus musculus) with significantly different Ne. We used the ratio of diversities at nonsynonymous and synonymous sites (dN/dS) to measure the harmful mutation load. Our results showed that this ratio observed for the admixed population was intermediate between those of the parental populations. The dN/dS ratio of the hybrid population was significantly higher than that of M. m. castaneus but lower than that of M. m. musculus. Our analysis revealed a significant positive correlation between the proportion of M. m. musculus ancestry in admixed individuals and their dN/dS ratio. This suggests that the admixed individuals with high proportions of M. m. musculus ancestry have large dN/dS ratios. We also used the proportion of deleterious nonsynonymous SNVs as a proxy for deleterious mutation load, which also produced similar results. The observed results were in concordance with those expected by theory. We also show a shift in the distribution of fitness effects of nonsynonymous SNVs in the admixed genomes compared to the parental populations. These findings suggest that the deleterious mutation load of the admixed population is determined by the proportion of the ancestries of the subspecies. Therefore, it is important to consider the status and the level of genetic admixture of the populations whilst estimating the mutation loads.

Deleterious Variation in Natural Populations and Implications for Conservation Genetics

Deleterious mutations decrease reproductive fitness and are ubiquitous in genomes. Given that many organisms face ongoing threats of extinction, there is interest in elucidating the impact of deleterious variation on extinction risk and optimizing management strategies accounting for such mutations. Quantifying deleterious variation and understanding the effects of population history on deleterious variation are complex endeavors because we do not know the strength of selection acting on each mutation. Further, the effect of demographic history on deleterious mutations depends on the strength of selection against the mutation and the degree of dominance. Here we clarify how deleterious variation can be quantified and studied in natural populations. We then discuss how different demographic factors, such as small population size, nonequilibrium population size changes, inbreeding, and gene flow, affect deleterious variation. Lastly, we provide guidance on studying deleterious variation in nonmodel populations of conservation concern.

Deleterious mutations and the rare allele burden on rice gene expression

Deleterious genetic variation is maintained in populations at low frequencies. Under a model of stabilizing selection, rare (and presumably deleterious) genetic variants are associated with increase or decrease in gene expression from some intermediate optimum. We investigate this phenomenon in a population of largely Oryza sativa ssp. indica rice landraces under normal unstressed wet and stressful drought field conditions. We include single nucleotide polymorphisms, insertion/deletion mutations, and structural variants in our analysis and find a stronger association between rare variants and gene expression outliers under the stress condition. We also show an association of the strength of this rare variant effect with linkage, gene expression levels, network connectivity, local recombination rate, and fitness consequence scores, consistent with the stabilizing selection model of gene expression.

The evolutionary patterns of barley pericentromeric chromosome regions, as shaped by linkage disequilibrium and domestication

The distribution of recombination events along large cereal chromosomes is uneven and is generally restricted to gene-rich telomeric ends. To understand how the lack of recombination affects diversity in the large pericentromeric regions, we analysed deep exome capture data from a final panel of 815 Hordeum vulgare (barley) cultivars, landraces and wild barleys, sampled from across their eco-geographical ranges. We defined and compared variant data across the pericentromeric and non-pericentromeric regions, observing a clear partitioning of diversity both within and between chromosomes and germplasm groups. Dramatically reduced diversity was found in the pericentromeres of both cultivars and landraces when compared with wild barley. We observed a mixture of completely and partially differentiated single-nucleotide polymorphisms (SNPs) between domesticated and wild gene pools, suggesting that domesticated gene pools were derived from multiple wild ancestors. Patterns of genome-wide linkage disequilibrium, haplotype block size and number, and variant frequency within blocks showed clear contrasts among individual chromosomes and between cultivars and wild barleys. Although most cultivar chromosomes shared a single major pericentromeric haplotype, chromosome 7H clearly differentiated the two-row and six-row types associated with different geographical origins. Within the pericentromeric regions we identified 22 387 non-synonymous SNPs, 92 of which were fixed for alternative alleles in cultivar versus wild accessions. Surprisingly, only 29 SNPs found exclusively in the cultivars were predicted to be 'highly deleterious'. Overall, our data reveal an unconventional pericentromeric genetic landscape among distinct barley gene pools, with different evolutionary processes driving domestication and diversification.

PON-All: Amino Acid Substitution Tolerance Predictor for All Organisms

Genetic variations are investigated in human and many other organisms for many purposes (e.g., to aid in clinical diagnosis). Interpretation of the identified variations can be challenging. Although some dedicated prediction methods have been developed and some tools for human variants can also be used for other organisms, the performance and species range have been limited. We developed a novel variant pathogenicity/tolerance predictor for amino acid substitutions in any organism. The method, PON-All, is a machine learning tool trained on human, animal, and plant variants. Two versions are provided, one with Gene Ontology (GO) annotations and another without these details. GO annotations are not available or are partial for many organisms of interest. The methods provide predictions for three classes: pathogenic, benign, and variants of unknown significance. On the blind test, when using GO annotations, accuracy was 0.913 and MCC 0.827. When GO features were not used, accuracy was 0.856 and MCC 0.712. The performance is the best for human and plant variants and somewhat lower for animal variants because the number of known disease-causing variants in animals is rather small. The method was compared to several other tools and was found to have superior performance. PON-All is freely available at http://structure.bmc.lu.se/PON-All and http://8.133.174.28:8999/.

Systematic prediction of EMS-induced mutations in a sorghum mutant population

The precise detection of causal DNA mutations (deoxyribonucleic acid) is very crucial for forward genetic studies. Several sources of errors contribute to false-positive detections by current variant-calling algorithms, which impact associating phenotypes with genotypes. To improve the accuracy of mutation detection, we implemented a binning method for the accurate detection of likely ethyl methanesulfonate (EMS)-induced mutations in a sequenced mutant population. We also implemented a clustering algorithm for detecting likely false negatives with high accuracy. Sorghum bicolor is a very valuable crop species with tremendous potential for uncovering novel gene functions associated with highly desirable agronomical traits. We demonstrate the precision of the described approach in the detection of likely EMS-induced mutations from the publicly available low-cost sequencing of the M₃ generation from 600 sorghum BTx623 mutants. The approach detected 3,274,606 single nucleotide polymorphisms (SNPs), of which 96% (3,141,908) were G/C to A/T DNA substitutions, as expected by EMS-mutagenesis mode of action. We demonstrated the general applicability of the described method and showed a high concordance, 94% (3,074,759) SNPs overlap between SAMtools-based and GATK-based variant-calling algorithms. Our clustering algorithm uncovered evidence for an additional 223,048 likely false-negative shared EMS-induced mutations. The final 3,497,654 SNPs represent an 87% increase in SNPs detected from the previous analysis of the mutant population, with an average of one SNP per 125 kb in the sorghum genome. Annotation of the final SNPs revealed 10,263 high-impact and 136,639 moderate-impact SNPs, including 7217 stop-gained mutations, which averages 12 stop-gained mutations per mutant, and four high- or medium-impact SNPs per sorghum gene. We have implemented a public search database for this new genetic resource of 30,285 distinct sorghum genes containing medium- or high-impact EMS-induced mutations. Seedstock for a select 486 of the 600 described mutants are publicly available in the Germplasm Resources Information Network (GRIN) database.

Improvement of prediction ability by integrating multi-omic datasets in barley

Background

Genomic prediction (GP) based on single nucleotide polymorphisms (SNP) has become a broadly used tool to increase the gain of selection in plant breeding. However, using predictors that are biologically closer to the phenotypes such as transcriptome and metabolome may increase the prediction ability in GP. The objectives of this study were to (i) assess the prediction ability for three yield-related phenotypic traits using different omic datasets as single predictors compared to a SNP array, where these omic datasets included different types of sequence variants (full-SV, deleterious-dSV, and tolerant-tSV), different types of transcriptome (expression presence/absence variation-ePAV, gene expression-GE, and transcript expression-TE) sampled from two tissues, leaf and seedling, and metabolites (M); (ii) investigate the improvement in prediction ability when combining multiple omic datasets information to predict phenotypic variation in barley breeding programs; (iii) explore the predictive performance when using SV, GE, and ePAV from simulated 3’end mRNA sequencing of different lengths as predictors.

Results

The prediction ability from genomic best linear unbiased prediction (GBLUP) for the three traits using dSV information was higher than when using tSV, all SV information, or the SNP array. Any predictors from the transcriptome (GE, TE, as well as ePAV) and metabolome provided higher prediction abilities compared to the SNP array and SV on average across the three traits. In addition, some (di)-similarity existed between different omic datasets, and therefore provided complementary biological perspectives to phenotypic variation. Optimal combining the information of dSV, TE, ePAV, as well as metabolites into GP models could improve the prediction ability over that of the single predictors alone.

Conclusions

The use of integrated omic datasets in GP model is highly recommended. Furthermore, we evaluated a cost-effective approach generating 3’end mRNA sequencing with transcriptome data extracted from seedling without losing prediction ability in comparison to the full-length mRNA sequencing, paving the path for the use of such prediction methods in commercial breeding programs.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08337-7).

Deleterious Mutations Accumulate Faster in Allopolyploid than Diploid Cotton (Gossypium) and Unequally between Subgenomes

Whole genome duplication (polyploidization) is among the most dramatic mutational processes in nature, so understanding how natural selection differs in polyploids relative to diploids is an important goal. Population genetics theory predicts that recessive deleterious mutations accumulate faster in allopolyploids than diploids due to the masking effect of redundant gene copies, but this prediction is hitherto unconfirmed. Here, we use the cotton genus (Gossypium), which contains seven allopolyploids derived from a single polyploidization event 1-2 million years ago, to investigate deleterious mutation accumulation. We use two methods of identifying deleterious mutations at the nucleotide and amino acid level, along with whole-genome resequencing of 43 individuals spanning six allopolyploid species and their two diploid progenitors, to demonstrate that deleterious mutations accumulate faster in allopolyploids than in their diploid progenitors. We find that, unlike what would be expected under models of demographic changes alone, strongly deleterious mutations show the biggest difference between ploidy levels, and this effect diminishes for moderately and mildly deleterious mutations. We further show that the proportion of nonsynonymous mutations that are deleterious differs between the two co-resident subgenomes in the allopolyploids, suggesting that homoeologous masking acts unequally between subgenomes. Our results provide a genome-wide perspective on classic notions of the significance of gene duplication that likely are broadly applicable to allopolyploids, with implications for our understanding of the evolutionary fate of deleterious mutations. Finally, we note that some measures of selection (e.g. dN/dS, πN/πS) may be biased when species of different ploidy levels are compared.

Fitness Effects of Mutations: An Assessment of PROVEAN Predictions Using Mutation Accumulation Data

Predicting fitness in natural populations is a major challenge in biology. It may be possible to leverage fast-accumulating genomic data sets to infer the fitness effects of mutant alleles, allowing evolutionary questions to be addressed in any organism. In this paper, we investigate the utility of one such tool, called PROVEAN. This program compares a query sequence with existing data to provide an alignment-based score for any protein variant, with scores categorized as neutral or deleterious based on a pre-set threshold. PROVEAN has been used widely in evolutionary studies, for example, to estimate mutation load in natural populations, but has not been formally tested as a predictor of aggregate mutational effects on fitness. Using three large published data sets on the genome sequences of laboratory mutation accumulation lines, we assessed how well PROVEAN predicted the actual fitness patterns observed, relative to other metrics. In most cases, we find that a simple count of the total number of mutant proteins is a better predictor of fitness than the number of proteins with variants scored as deleterious by PROVEAN. We also find that the sum of all mutant protein scores explains variation in fitness better than the number of mutant proteins in one of the data sets. We discuss the implications of these results for studies of populations in the wild.

Gene network simulations provide testable predictions for the molecular domestication syndrome

The domestication of plant species lead to repeatable morphological evolution, often referred to as the phenotypic domestication syndrome. Domestication is also associated with important genomic changes, such as the loss of genetic diversity compared to adequately large wild populations, and modifications of gene expression patterns. Here, we explored theoretically the effect of a domestication-like scenario on the evolution of gene regulatory networks. We ran population genetics simulations in which individuals were featured by their genotype (an interaction matrix encoding a gene regulatory network) and their gene expressions, representing the phenotypic level. Our domestication scenario included a population bottleneck and a selection switch mimicking human-mediated directional and canalizing selection, i.e., change in the optimal gene expression level and selection towards more stable expression across environments. We showed that domestication profoundly alters genetic architectures. Based on four examples of plant domestication scenarios, our simulations predict (i) a drop in neutral allelic diversity, (ii) a change in gene expression variance that depends upon the domestication scenario, (iii) transient maladaptive plasticity, (iv) a deep rewiring of the gene regulatory networks, with a trend towards gain of regulatory interactions, and (v) a global increase in the genetic correlations among gene expressions, with a loss of modularity in the resulting coexpression patterns and in the underlying networks. We provide empirically testable predictions on the differences of genetic architectures between wild and domesticated forms. The characterization of such systematic evolutionary changes in the genetic architecture of traits contributes to define a molecular domestication syndrome.

Genome optimization via virtual simulation to accelerate maize hybrid breeding

The employment of doubled-haploid (DH) technology in maize has vastly accelerated the efficiency of developing inbred lines. The selection of superior lines has to rely on genotypes with genomic selection (GS) model, rather than phenotypes due to the high expense of field phenotyping. In this work, we implemented 'genome optimization via virtual simulation (GOVS)' using the genotype and phenotype data of 1404 maize lines and their F1 progeny. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' or 'advantageous alleles' in a genetic pool. Such a virtually optimized genome, although can never be developed in reality, may help plot the optimal route to direct breeding decisions. GOVS assists in the selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. The assumption is that the more fragments of optimal genotypes a line contributes to the assembly, the higher the likelihood of the line favored in the F1 phenotype, e.g. grain yield. Compared to traditional GS method, GOVS-assisted selection may avoid using an arbitrary threshold for the predicted F1 yield to assist selection. Additionally, the selected lines contributed complementary sets of advantageous alleles to the virtual genome. This feature facilitates plotting the optimal route for DH production, whereby the fewest lines and F1 combinations are needed to pyramid a maximum number of advantageous alleles in the new DH lines. In summary, incorporation of DH production, GS and genome optimization will ultimately improve genomically designed breeding in maize. Short abstract: Doubled-haploid (DH) technology has been widely applied in maize breeding industry, as it greatly shortens the period of developing homozygous inbred lines via bypassing several rounds of self-crossing. The current challenge is how to efficiently screen the large volume of inbred lines based on genotypes. We present the toolbox of genome optimization via virtual simulation (GOVS), which complements the traditional genomic selection model. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' in a breeding population, and then assists in selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. Availability of GOVS (https://govs-pack.github.io/) to the public may ultimately facilitate genomically designed breeding in maize.

Deleterious protein-coding variants in diverse cattle breeds of the world

The domestication of wild animals has resulted in a reduction in effective population sizes, which can affect the deleterious mutation load of domesticated breeds. In addition, artificial selection contributes to the accumulation of deleterious mutations because of an increased rate of inbreeding among domesticated animals. Since founder population sizes and artificial selection differ between cattle breeds, their deleterious mutation load can vary. We investigated this question by using whole-genome data from 432 animals belonging to 54 worldwide cattle breeds. Our analysis revealed a negative correlation between genomic heterozygosity and nonsynonymous-to-silent diversity ratio, which suggests a higher proportion of single nucleotide variants (SNVs) affecting proteins in low-diversity breeds. Our results also showed that low-diversity breeds had a larger number of high-frequency (derived allele frequency (DAF) > 0.51) deleterious SNVs than high-diversity breeds. An opposite trend was observed for the low-frequency (DAF ≤ 0.51) deleterious SNVs. Overall, the number of high-frequency deleterious SNVs was larger in the genomes of taurine cattle breeds than of indicine breeds, whereas the number of low-frequency deleterious SNVs was larger in the genomes of indicine cattle than in those of taurine cattle. Furthermore, we observed significant variation in the counts of deleterious SNVs within taurine breeds. The variations in deleterious mutation load between taurine and indicine breeds could be attributed to the population sizes of the wild progenitors before domestication, whereas the variations observed within taurine breeds could be due to differences in inbreeding level, strength of artificial selection, and/or founding population size. Our findings imply that the incidence of genetic diseases can vary between cattle breeds.

Chromosome-level genome assembly and population genetic analysis of a critically endangered rhododendron provide insights into its conservation

Rhododendrons are woody plants, famous throughout the world as having high horticultural value. However, many wild species are currently threatened with extinction. Here, we report for the first time a high-quality, chromosome-level genome of Rhododendron griersonianum, which has contributed to approximately 10% of all horticultural rhododendron varieties but which in its wild form has been evaluated as critically endangered. The final genome assembly, which has a contig N50 size of approximately 34 M and a total length of 677 M, is the highest-quality genome sequenced within the genus to date, in part due to its low heterozygosity (0.18%). Identified repeats constitute approximately 57% of the genome, and 38 280 protein-coding genes were predicted with high support. We further resequenced 31 individuals of R. griersonianum as well as 30 individuals of its widespread relative R. delavayi, and performed additional conservation genomic analysis. The results showed that R. griersonianum had lower genetic diversity (θ = 2.58e-3; π = 1.94e-3) when compared not only to R. delavayi (θ = 11.61e-3, π = 12.97e-3), but also to most other woody plants. Furthermore, three severe genetic bottlenecks were detected using both the Stairway plot and fastsimcoal2 analysis, which are thought to have occurred in the late Middle Pleistocene and the Last Glacial Maximum (LGM) period. After these bottlenecks, R. griersonianum recovered and maintained a constant effective population size (>25 000) until now. Intriguingly, R. griersonianum has accumulated significantly more deleterious mutations in the homozygous state than R. delavayi, and several deleterious mutations (e.g., in genes involved in the response to heat stress) are likely to have harmed the adaptation of this plant to its surroundings. This high-quality, chromosome-level genome and the population genomic analysis of the critically endangered R. griersonianum will provide an invaluable resource as well as insights for future study in this species to facilitate conservation and in the genus Rhododendron in general.

Measurements of lethal and nonlethal inbreeding depression inform the de novo domestication of Silphium integrifolium

PREMISE

Inbreeding depression, or the reduction in fitness of progeny with related parents, has the potential to adversely affect the long-term viability of both wild and captive plant populations. Silphium integrifolium, a prairie plant native to the central United States, has been identified as a potential candidate for domestication as a perennial oilseed crop. Little is known about the potential for inbreeding depression in this species, but it is expected to be nonnegligible because S. integrifolium is both perennial and self-incompatible. Here, we measure lethal inbreeding depression expressed through embryo deaths, and nonlethal inbreeding depression expressed through changes in vigor and fitness phenotypes of progeny.

METHODS

First, we made controlled crosses among related and unrelated individuals to determine the effect of two different levels of inbreeding on seed production. Then, we grew inbred and outbred progeny from this population to reproductive maturity and measured 11 key traits.

RESULTS

We found that within an improved S. integrifolium population, individuals carried an average of slightly less than one lethal allele per gamete. In progeny, significant inbreeding depression was observed in at least one family for eight of the 11 measured traits.

CONCLUSIONS

Inbreeding depression is likely to be an important challenge to S. integrifolium domestication, reducing overall population fecundity and values for important phenotypes. These effects may grow worse as selection reduces effective population size. We recommend several strategies for S. integrifolium breeding to help mitigate these problems.

The patterns of deleterious mutations during the domestication of soybean

Globally, soybean is a major protein and oil crop. Enhancing our understanding of the soybean domestication and improvement process helps boost genomics-assisted breeding efforts. Here we present a genome-wide variation map of 10.6 million single-nucleotide polymorphisms and 1.4 million indels for 781 soybean individuals which includes 418 domesticated (Glycine max), 345 wild (Glycine soja), and 18 natural hybrid (G. max/G. soja) accessions. We describe the enhanced detection of 183 domestication-selective sweeps and the patterns of putative deleterious mutations during domestication and improvement. This predominantly selfing species shows 7.1% reduction of overall deleterious mutations in domesticated soybean relative to wild soybean and a further 1.4% reduction from landrace to improved accessions. The detected domestication-selective sweeps also show reduced levels of deleterious alleles. Importantly, genotype imputation with this resource increases the mapping resolution of genome-wide association studies for seed protein and oil traits in a soybean diversity panel.

Harnessing Knowledge from Maize and Rice Domestication for New Crop Breeding

Crop domestication has fundamentally altered the course of human history, causing a shift from hunter-gatherer to agricultural societies and stimulating the rise of modern civilization. A greater understanding of crop domestication would provide a theoretical basis for how we could improve current crops and develop new crops to deal with environmental challenges in a sustainable manner. Here, we provide a comprehensive summary of the similarities and differences in the domestication processes of maize and rice, two major staple food crops that feed the world. We propose that maize and rice might have evolved distinct genetic solutions toward domestication. Maize and rice domestication appears to be associated with distinct regulatory and evolutionary mechanisms. Rice domestication tended to select de novo, loss-of-function, coding variation, while maize domestication more frequently favored standing, gain-of-function, regulatory variation. At the gene network level, distinct genetic paths were used to acquire convergent phenotypes in maize and rice domestication, during which different central genes were utilized, orthologous genes played different evolutionary roles, and unique genes or regulatory modules were acquired for establishing new traits. Finally, we discuss how the knowledge gained from past domestication processes, together with emerging technologies, could be exploited to improve modern crop breeding and domesticate new crops to meet increasing human demands.

Evolutionary insights into plant breeding

Crop domestication is a fascinating area of study, as shown by a multitude of recent reviews. Coupled with the increasing availability of genomic and phenomic resources in numerous crop species, insights from evolutionary biology will enable a deeper understanding of the genetic architecture and short-term evolution of complex traits, which can be used to inform selection strategies. Future advances in crop improvement will rely on the integration of population genetics with plant breeding methodology, and the development of community resources to support research in a variety of crop life histories and reproductive strategies. We highlight recent advances related to the role of selective sweeps and demographic history in shaping genetic architecture, how these breakthroughs can inform selection strategies, and the application of precision gene editing to leverage these connections.

Gene Expression Modularity Reveals Footprints of Polygenic Adaptation in Theobroma cacao

Separating footprints of adaptation from demography is challenging. When selection has acted on a single locus with major effect, this issue can be alleviated through signatures left by selective sweeps. However, as adaptation is often driven by small allele frequency shifts at many loci, studies focusing on single genes are able to identify only a small portion of genomic variants responsible for adaptation. In face of this challenge, we utilize coexpression information to search for signals of polygenetic adaptation in Theobroma cacao, a tropical tree species that is the source of chocolate. Using transcriptomics and a weighted correlation network analysis, we group genes with similar expression patterns into functional modules. We then ask whether modules enriched for specific biological processes exhibit cumulative effects of differential selection in the form of high FST and dXY between populations. Indeed, modules putatively involved in protein modification, flowering, and water transport show signs of polygenic adaptation even though individual genes that are members of those groups do not bear strong signatures of selection. Modeling of demography, background selection, and the effects of genomic features reveal that these patterns are unlikely to arise by chance. We also find that specific modules are enriched for signals of strong or relaxed purifying selection, with one module bearing signs of adaptive differentiation and an excess of deleterious mutations. Our results provide insight into polygenic adaptation and contribute to understanding of population structure, demographic history, and genome evolution in T. cacao.

The type of bottleneck matters: Insights into the deleterious variation landscape of small managed populations

Predictions about the consequences of a small population size on genetic and deleterious variation are fundamental to population genetics. As small populations are more affected by genetic drift, purifying selection acting against deleterious alleles is predicted to be less efficient, therefore increasing the risk of inbreeding depression. However, the extent to which small populations are subjected to genetic drift depends on the nature and time frame in which the bottleneck occurs. Domesticated species are an excellent model to investigate the consequences of population bottlenecks on genetic and deleterious variation in small populations. This is because their history is dominated by known bottlenecks associated with domestication, breed formation and intense selective breeding. Here, we use whole-genome sequencing data from 97 chickens representing 39 traditional fancy breeds to directly examine the consequences of two types of bottlenecks for deleterious variation: the severe domestication bottleneck and the recent population decline accompanying breed formation. We find that recently bottlenecked populations have a higher proportion of deleterious variants relative to populations that have been kept at small population sizes since domestication. We also observe that long tracts of homozygous genotypes (runs of homozygosity) are proportionally more enriched in deleterious variants than the rest of the genome. This enrichment is particularly evident in recently bottlenecked populations, suggesting that homozygosity of these variants is likely to occur due to genetic drift and recent inbreeding. Our results indicate that the timing and nature of population bottlenecks can substantially shape the deleterious variation landscape in small populations.

The Fate of Deleterious Variants in a Barley Genomic Prediction Population

Targeted identification and purging of deleterious genetic variants has been proposed as a novel approach to animal and plant breeding. This strategy is motivated, in part, by the observation that demographic events and strong selection associated with cultivated species pose a "cost of domestication." This includes an increase in the proportion of genetic variants that are likely to reduce fitness. Recent advances in DNA resequencing and sequence constraint-based approaches to predict the functional impact of a mutation permit the identification of putatively deleterious SNPs (dSNPs) on a genome-wide scale. Using exome capture resequencing of 21 barley lines, we identified 3855 dSNPs among 497,754 total SNPs. We generated whole-genome resequencing data of Hordeum murinum ssp. glaucum as a phylogenetic outgroup to polarize SNPs as ancestral vs. derived. We also observed a higher proportion of dSNPs per synonymous SNPs (sSNPs) in low-recombination regions of the genome. Using 5215 progeny from a genomic prediction experiment, we examined the fate of dSNPs over three breeding cycles. Adjusting for initial frequency, derived alleles at dSNPs reduced in frequency or were lost more often than other classes of SNPs. The highest-yielding lines in the experiment, as chosen by standard genomic prediction approaches, carried fewer homozygous dSNPs than randomly sampled lines from the same progeny cycle. In the final cycle of the experiment, progeny selected by genomic prediction had a mean of 5.6% fewer homozygous dSNPs relative to randomly chosen progeny from the same cycle.

Environmental Association Identifies Candidates for Tolerance to Low Temperature and Drought

Barley (Hordeum vulgare ssp. vulgare) is cultivated from the equator to the Arctic Circle. The wild progenitor species, Hordeum vulgare ssp. spontaneum, occupies a relatively narrow latitudinal range (∼30 - 40° N) primarily at low elevation (< 1,500 m). Adaptation to the range of cultivation has occurred over ∼8,000 years. The genetic basis of adaptation is amenable to study through environmental association. An advantage of environmental association in a well-characterized crop is that many loci that contribute to climatic adaptation and abiotic stress tolerance have already been identified. This provides the opportunity to determine if environmental association approaches effectively identify these loci of large effect. Using published genotyping from 7,864 SNPs in 803 barley landraces, we examined allele frequency differentiation across multiple partitions of the data and mixed model associations relative to bioclimatic variables. Using newly generated resequencing data from a subset of these landraces, we tested for linkage disequilibrium (LD) between SNPs queried in genotyping and SNPs in neighboring loci. Six loci previously reported to contribute to adaptive differences in flowering time and abiotic stress in barley and six loci previously identified in other plant species were identified in our analyses. In many cases, patterns of LD are consistent with the causative variant occurring in the immediate vicinity of the queried SNP. The identification of barley orthologs to well-characterized genes may provide a new understanding of the nature of adaptive variation and could permit a more targeted use of potentially adaptive variants in barley breeding and germplasm improvement.

Development of a Multiparent Population for Genetic Mapping and Allele Discovery in Six-Row Barley

Germplasm collections hold valuable allelic diversity for crop improvement and genetic mapping of complex traits. To gain access to the genetic diversity within the USDA National Small Grain Collection (NSGC), we developed the Barley Recombinant Inbred Diverse Germplasm Population (BRIDG6), a six-row spring barley multiparent population (MPP) with 88 cultivated accessions crossed to a common parent (Rasmusson). The parents were randomly selected from a core subset of the NSGC that represents the genetic diversity of landrace and breeding accessions. In total, we generated 6160 F5 recombinant inbred lines (RILs), with an average of 69 and a range of 37-168 RILs per family, that were genotyped with 7773 SNPs, with an average of 3889 SNPs segregating per family. We detected 23 quantitative trait loci (QTL) associated with flowering time with five QTL found coincident with previously described flowering time genes. A major QTL was detected near the flowering time gene, HvPpd-H1 which affects photoperiod. Haplotype-based analysis of HvPpd-H1 identified private alleles to families of Asian origin conferring both positive and negative effects, providing the first observation of flowering time-related alleles private to Asian accessions. We evaluated several subsampling strategies to determine the effect of sample size on the power of QTL detection, and found that, for flowering time in barley, a sample size >50 families or 3000 individuals results in the highest power for QTL detection. This MPP will be useful for uncovering large and small effect QTL for traits of interest, and identifying and utilizing valuable alleles from the NSGC for barley improvement.

Elevated mutation and selection in wild emmer wheat in response to 28 years of global warming

The realized threats of global warming to biodiversity have catalyzed the search for a solution to protect and conserve extant plant genetic resources. Part of the solution, however, is dependent on the knowledge of how plant populations respond genetically to these threats, which is largely lacking. We conducted a unique genomic characterization of genetic responses in 10 wild emmer wheat populations in Israel that were sampled twice in 1980 and 2008. After the 28 y of global warming, these populations displayed elevated selection, reduced diversity and temporal divergence, and carried increased mutational burdens forward. However, some populations still showed the ability to acquire beneficial alleles for future adaptation. The patterns of genetic response to rainfall and temperature were complex.

Global warming has been documented to threaten wild plants with strong selection pressures, but how plant populations respond genetically to the threats remains poorly understood. We characterized the genetic responses of 10 wild emmer wheat (Triticum dicoccoides Koern.; WEW) populations in Israel, sampling them in 1980 and again in 2008, through an exome capture analysis. It was found that these WEW populations were under elevated selection, displayed reduced diversity and temporal divergence, and carried increased mutational burdens forward. However, some populations still showed the ability to acquire beneficial alleles via selection or de novo mutation for future adaptation. Grouping populations with mean annual rainfall and temperature revealed significant differences in most of the 14 genetic estimates in either sampling year or over the 28 y. The patterns of genetic response to rainfall and temperature varied and were complex. In general, temperature groups displayed more temporal differences in genetic response than rainfall groups. The highest temperature group had more deleterious single nucleotide polymorphisms (dSNPs), higher nucleotide diversity, fewer selective sweeps, lower differentiation, and lower mutational burden. The least rainfall group had more dSNPs, higher nucleotide diversity, lower differentiation and higher mutational burden. These characterized genetic responses are significant, allowing not only for better understanding of evolutionary changes in the threatened populations, but also for realistic modeling of plant population adaptability and vulnerability to global warming.

Progressive heterosis in genetically defined tetraploid maize

Progressive heterosis, i.e., the additional hybrid vigor in double-cross tetraploid hybrids not found in their single-cross tetraploid parents, has been documented in a number of species including alfalfa, potato, and maize. In this study, four artificially induced maize tetraploids, directly derived from standard inbred lines, were crossed in pairs to create two single-cross hybrids. These hybrids were then crossed to create double-cross hybrids containing genetic material from all four original lines. Replicated field-based phenotyping of the materials over four years indicated a strong progressive heterosis phenotype in tetraploids but not in their diploid counterparts. In particular, the above ground dry weight phenotype of double-cross tetraploid hybrids was on average 34% and 56% heavier than that of the single-cross tetraploid hybrids and the double-cross diploid counterparts, respectively. Additionally, whole-genome resequencing of the original inbred lines and further analysis of these data did not show the expected spectrum of alleles to explain tetraploid progressive heterosis under the complementation of complete recessive model. These results underscore the reality of the progressive heterosis phenotype, its potential utility for increasing crop biomass production, and the need for exploring alternative hypothesis to explain it at a molecular level.

De Novo Domestication: An Alternative Route toward New Crops for the Future

Current global agricultural production must feed over 7 billion people. However, productivity varies greatly across the globe and is under threat from both increased competitions for land and climate change and associated environmental deterioration. Moreover, the increase in human population size and dietary changes are putting an ever greater burden on agriculture. The majority of this burden is met by the cultivation of a very small number of species, largely in locations that differ from their origin of domestication. Recent technological advances have raised the possibility of de novo domestication of wild plants as a viable solution for designing ideal crops while maintaining food security and a more sustainable low-input agriculture. Here we discuss how the discovery of multiple key domestication genes alongside the development of technologies for accurate manipulation of several target genes simultaneously renders de novo domestication a route toward crops for the future.

Exome sequencing highlights the role of wild-relative introgression in shaping the adaptive landscape of the wheat genome

Introgression is a potential source of beneficial genetic diversity. The contribution of introgression to adaptive evolution and improvement of wheat as it was disseminated worldwide remains unknown. We used targeted re-sequencing of 890 diverse accessions of hexaploid and tetraploid wheat to identify wild-relative introgression. Introgression, and selection for improvement and environmental adaptation, each reduced deleterious allele burden. Introgression increased diversity genome wide and in regions harboring major agronomic genes, and contributed alleles explaining a substantial proportion of phenotypic variation. These results suggest that historic gene flow from wild relatives made a substantial contribution to the adaptive diversity of modern bread wheat.

Accelerating crop genetic gains with genomic selection

Genomic prediction based on additive genetic effects can accelerate genetic gain. There are opportunities for further improvement by including non-additive effects that access untapped sources of genetic diversity. Several studies have reported a worrying gap between the projected global future demand for plant-based products and the current annual rates of production increase, indicating that enhancing the rate of genetic gain might be critical for future food security. Therefore, new breeding technologies and strategies are required to significantly boost genetic improvement of future crop cultivars. Genomic selection (GS) has delivered considerable genetic gain in animal breeding and is becoming an essential component of many modern plant breeding programmes as well. In this paper, we review the lessons learned from implementing GS in livestock and the impact of GS on crop breeding, and discuss important features for the success of GS under different breeding scenarios. We highlight major challenges associated with GS including rapid genotyping, phenotyping, genotype-by-environment interaction and non-additivity and give examples for opportunities to overcome these issues. Finally, the potential of combining GS with other modern technologies in order to maximise the rate of crop genetic improvement is discussed, including the potential of increasing prediction accuracy by integration of crop growth models in GS frameworks.

Deleterious Mutation Burden and Its Association with Complex Traits in Sorghum (Sorghum bicolor)

Sorghum (Sorghum bicolor (L.) Moench) is a major staple food cereal for millions of people worldwide. Valluru et al. identify putative deleterious mutations among ∼5.5M segregating variants of 229 diverse sorghum...

Sorghum (Sorghum bicolor L.) is a major food cereal for millions of people worldwide. The sorghum genome, like other species, accumulates deleterious mutations, likely impacting its fitness. The lack of recombination, drift, and the coupling with favorable loci impede the removal of deleterious mutations from the genome by selection. To study how deleterious variants impact phenotypes, we identified putative deleterious mutations among ∼5.5 M segregating variants of 229 diverse biomass sorghum lines. We provide the whole-genome estimate of the deleterious burden in sorghum, showing that ∼33% of nonsynonymous substitutions are putatively deleterious. The pattern of mutation burden varies appreciably among racial groups. Across racial groups, the mutation burden correlated negatively with biomass, plant height, specific leaf area (SLA), and tissue starch content (TSC), suggesting that deleterious burden decreases trait fitness. Putatively deleterious variants explain roughly one-half of the genetic variance. However, there is only moderate improvement in total heritable variance explained for biomass (7.6%) and plant height (average of 3.1% across all stages). There is no advantage in total heritable variance for SLA and TSC. The contribution of putatively deleterious variants to phenotypic diversity therefore appears to be dependent on the genetic architecture of traits. Overall, these results suggest that incorporating putatively deleterious variants into genomic models slightly improves prediction accuracy because of extensive linkage. Knowledge of deleterious variants could be leveraged for sorghum breeding through either genome editing and/or conventional breeding that focuses on the selection of progeny with fewer deleterious alleles.

Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references

Genotyping-by-sequencing (GBS) provides high SNP coverage and has recently emerged as a popular technology for genetic and breeding applications in bread wheat (Triticum aestivum L.) and many other plant species. Although GBS can discover millions of SNPs, a high rate of missing data is a major concern for many applications. Accurate imputation of those missing data can significantly improve the utility of GBS data. This study compared imputation accuracies among four genome references including three wheat references (Chinese Spring survey sequence, W7984, and IWGSC RefSeq v1.0) and one barley reference genome by comparing imputed data derived from low-depth sequencing to actual data from high-depth sequencing. After imputation, the average number of imputed data points was the highest in the B genome (~48.99%). The D genome had the lowest imputed data points (~15.02%) but the highest imputation accuracy. Among the four reference genomes, IWGSC RefSeq v1.0 reference provided the most imputed data points, but the lowest imputation accuracy for the SNPs with < 10% minor allele frequency (MAF). The W7984 reference, however, provided the highest imputation accuracy for the SNPs with < 10% MAF.

Deleterious alleles in the context of domestication, inbreeding, and selection

Each individual has a certain number of harmful mutations in its genome. These mutations can lower the fitness of the individual carrying them, dependent on their dominance and selection coefficient. Effective population size, selection, and admixture are known to affect the occurrence of such mutations in a population. The relative roles of demography and selection are a key in understanding the process of adaptation. These are factors that are potentially influenced and confounded in domestic animals. Here, we hypothesize that the series of events of bottlenecks, introgression, and strong artificial selection associated with domestication increased mutational load in domestic species. Yet, mutational load is hard to quantify, so there are very few studies available revealing the relevance of evolutionary processes. The precise role of artificial selection, bottlenecks, and introgression in further increasing the load of deleterious variants in animals in breeding and conservation programmes remains unclear. In this paper, we review the effects of domestication and selection on mutational load in domestic species. Moreover, we test some hypotheses on higher mutational load due to domestication and selective sweeps using sequence data from commercial pig and chicken lines. Overall, we argue that domestication by itself is not a prerequisite for genetic erosion, indicating that fitness potential does not need to decline. Rather, mutational load in domestic species can be influenced by many factors, but consistent or strong trends are not yet clear. However, methods emerging from molecular genetics allow discrimination of hypotheses about the determinants of mutational load, such as effective population size, inbreeding, and selection, in domestic systems. These findings make us rethink the effect of our current breeding schemes on fitness of populations.

Genomic effects of population collapse in a critically endangered ironwood tree Ostrya rehderiana

Increased human activity and climate change are driving numerous tree species to endangered status, and in the worst cases extinction. Here we examine the genomic signatures of the critically endangered ironwood tree Ostrya rehderiana and its widespread congener O. chinensis. Both species have similar demographic histories prior to the Last Glacial Maximum (LGM); however, the effective population size of O. rehderiana continued to decrease through the last 10,000 years, whereas O. chinensis recovered to Pre-LGM numbers. O. rehderiana accumulated more deleterious mutations, but purged more severely deleterious recessive variations than in O. chinensis. This purging and the gradually reduced inbreeding depression together may have mitigated extinction and contributed to the possible future survival of the outcrossing O. rehderiana. Our findings provide critical insights into the evolutionary history of population collapse and the potential for future recovery of the endangered trees.

Identification of candidate domestication-related genes with a systematic survey of loss-of-function mutations

Domestication is an important key co-evolutionary process through which humans have extensively altered the genomic make-up and appearance of both plants and animals. The identification of domestication-related genes remains very arduous. In this study, we present a systematic analytical approach that harnesses two recent advances in genomics, whole-genome sequencing (WGS) and prediction of loss-of-function (LOF) mutations, to greatly facilitate the assembly of an enriched catalogue of domestication-related candidate genes. Using WGS data for 296 cultivated (Glycine max) and 64 wild soybean accessions, we identified 8699 LOF variants, and 116 genes that are uniquely fixed for one or more LOF allele(s) in domesticated soybeans. Existing soybean transcriptomic data led us to overcome analytical challenges associated with whole-genome duplications and to identify neo- or subfunctionalized genes. This systematic approach allowed us to identify 110 candidate domestication-related genes in an efficient and rapid way. This catalogue contains previously well characterized domestication genes in soybean, as well as some orthologs from other domesticated crop species. In addition, it comprises many promising candidate domestication genes. Overall, this collection of candidate domestication-related genes in soybean is almost twice as large as the sum of all previously reported candidate genes in all other crops. We believe this systematic approach could readily be used in wide range of species.

Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants

Recent advances in genome resequencing have led to increased interest in prediction of the functional consequences of genetic variants. Variants at phylogenetically conserved sites are of particular interest, because they are more likely than variants at phylogenetically variable sites to have deleterious effects on fitness and contribute to phenotypic variation. Numerous comparative genomic approaches have been developed to predict deleterious variants, but the approaches are nearly always assessed based on their ability to identify known disease-causing mutations in humans. Determining the accuracy of deleterious variant predictions in nonhuman species is important to understanding evolution, domestication, and potentially to improving crop quality and yield. To examine our ability to predict deleterious variants in plants we generated a curated database of 2,910 Arabidopsis thaliana mutants with known phenotypes. We evaluated seven approaches and found that while all performed well, their relative ranking differed from prior benchmarks in humans. We conclude that deleterious mutations can be reliably predicted in A. thaliana and likely other plant species, but that the relative performance of various approaches does not necessarily translate from one species to another.

Demography and its effects on genomic variation in crop domestication

Over two thousand plant species have been modified morphologically through cultivation and human use. Here, we review three aspects of crop domestication that are currently undergoing marked revisions, due to analytical advancements and their application to whole genome resequencing (WGS) data. We begin by discussing the duration and demographic history of domestication. There has been debate as to whether domestication occurred quickly or slowly. The latter is tentatively supported both by fossil data and application of WGS data to sequentially Markovian coalescent methods that infer the history of effective population size. This history suggests the possibility of extended human impacts on domesticated lineages prior to their purposeful cultivation. We also make the point that demographic history matters, because it shapes patterns and levels of extant genetic diversity. We illustrate this point by discussing the evolutionary processes that contribute to the empirical observation that most crops examined to date have more putatively deleterious alleles than their wild relatives. These deleterious alleles may contribute to genetic load within crops and may be fitting targets for crop improvement. Finally, the same demographic factors are likely to shape the spectrum of structural variants (SVs) within crops. SVs are known to underlie many of the phenotypic changes associated with domestication and crop improvement, but we currently lack sufficient knowledge about the mechanisms that create SVs, their rates of origin, their population frequencies and their phenotypic effects.

Are Nonsense Alleles of Drosophila melanogaster Genes under Any Selection?

A gene which carries a bona fide loss-of-function mutation effectively becomes a functionless pseudogene, free from selective constraint. However, there is a number of molecular mechanisms that may lead to at least a partial preservation of the function of genes carrying even drastic alleles. We performed a direct measurement of the strength of negative selection acting on nonsense alleles of protein-coding genes in the Zambian population of Drosophila melanogaster. Within those exons that carry nonsense mutations, negative selection, assayed by the ratio of missense over synonymous nucleotide diversity levels, appears to be absent, consistent with total loss of function. In other exons of nonsense alleles, negative selection was deeply relaxed but likely not completely absent, and the per site number of missense alleles declined significantly with the distance from the premature stop codon. This pattern may be due to alternative splicing which preserves function of some isoforms of nonsense alleles of genes.

Dysregulation of expression correlates with rare-allele burden and fitness loss in maize

Here we report a multi-tissue gene expression resource that represents the genotypic and phenotypic diversity of modern inbred maize, and includes transcriptomes in an average of 255 lines in seven tissues. We mapped expression quantitative trait loci and characterized the contribution of rare genetic variants to extremes in gene expression. Some of the new mutations that arise in the maize genome can be deleterious; although selection acts to keep deleterious variants rare, their complete removal is impeded by genetic linkage to favourable loci and by finite population size. Modern maize breeders have systematically reduced the effects of this constant mutational pressure through artificial selection and self-fertilization, which have exposed rare recessive variants in elite inbred lines. However, the ongoing effect of these rare alleles on modern inbred maize is unknown. By analysing this gene expression resource and exploiting the extreme diversity and rapid linkage disequilibrium decay of maize, we characterize the effect of rare alleles and evolutionary history on the regulation of expression. Rare alleles are associated with the dysregulation of expression, and we correlate this dysregulation to seed-weight fitness. We find enrichment of ancestral rare variants among expression quantitative trait loci mapped in modern inbred lines, which suggests that historic bottlenecks have shaped regulation. Our results suggest that one path for further genetic improvement in agricultural species lies in purging the rare deleterious variants that have been associated with crop fitness.

Elevated Proportions of Deleterious Genetic Variation in Domestic Animals and Plants

A fraction of genetic variants segregating in any population are deleterious, which negatively impacts individual fitness. The domestication of animals and plants is associated with population bottlenecks and artificial selection, which are predicted to increase the proportion of deleterious variants. However, the extent to which this is a general feature of domestic species is unclear. Here, we examine the effects of domestication on the prevalence of deleterious variation using pooled whole-genome resequencing data from five domestic animal species (dog, pig, rabbit, chicken, and silkworm) and two domestic plant species (rice and soybean) compared with their wild ancestors. We find significantly reduced genetic variation and increased proportion of nonsynonymous amino acid changes in all but one of the domestic species. These differences are observable across a range of allele frequencies, both common and rare. We find proportionally more single nucleotide polymorphisms in highly conserved elements in domestic species and a tendency for domestic species to harbor a higher proportion of changes classified as damaging. Our findings most likely reflect an increased incidence of deleterious variants in domestic species, which is most likely attributable to population bottlenecks that lead to a reduction in the efficacy of selection. An exception to this pattern is displayed by European domestic pigs, which do not show traces of a strong population bottleneck and probably continued to exchange genes with wild boar populations after domestication. The results presented here indicate that an elevated proportion of deleterious variants is a common, but not ubiquitous, feature of domestic species.

A Pipeline for Classifying Deleterious Coding Mutations in Agricultural Plants

The impact of deleterious variation on both plant fitness and crop productivity is not completely understood and is a hot topic of debates. The deleterious mutations in plants have been solely predicted using sequence conservation methods rather than function-based classifiers due to lack of well-annotated mutational datasets in these organisms. Here, we developed a machine learning classifier based on a dataset of deleterious and neutral mutations in Arabidopsis thaliana by extracting 18 informative features that discriminate deleterious mutations from neutral, including 9 novel features not used in previous studies. We examined linear SVM, Gaussian SVM, and Random Forest classifiers, with the latter performing best. Random Forest classifiers exhibited a markedly higher accuracy than the popular PolyPhen-2 tool in the Arabidopsis dataset. Additionally, we tested whether the Random Forest, trained on the Arabidopsis dataset, accurately predicts deleterious mutations in Orýza sativa and Pisum sativum and observed satisfactory levels of performance accuracy (87% and 93%, respectively) higher than obtained by the PolyPhen-2. Application of Transfer learning in classifiers did not improve their performance. To additionally test the performance of the Random Forest classifier across different angiosperm species, we applied it to annotate deleterious mutations in Cicer arietinum and validated them using population frequency data. Overall, we devised a classifier with the potential to improve the annotation of putative functional mutations in QTL and GWAS hit regions, as well as for the evolutionary analysis of proliferation of deleterious mutations during plant domestication; thus optimizing breeding improvement and development of new cultivars.

Bioinformatically predicted deleterious mutations reveal complementation in the interior spruce hybrid complex

BACKGROUND

Mutation load is expected to be reduced in hybrids via complementation of deleterious alleles. While local adaptation of hybrids confounds phenotypic tests for reduced mutation load, it may be possible to assess variation in load by analyzing the distribution of putatively deleterious alleles. Here, we use this approach in the interior spruce (Picea glauca x P. engelmannii) hybrid complex, a group likely to suffer from high mutation load and in which hybrids exhibit local adaptation to intermediate conditions. We used PROVEAN to bioinformatically predict whether non-synonymous alleles are deleterious, based on conservation of the position and abnormality of the amino acid change.

RESULTS

As expected, we found that predicted deleterious alleles were at lower average allele frequencies than alleles not predicted to be deleterious. We were unable to detect a phenotypic effect on juvenile growth rate of the many rare alleles predicted to be deleterious. Both the proportion of alleles predicted to be deleterious and the proportion of loci homozygous for predicted deleterious alleles were higher in P. engelmannii (Engelmann spruce) than in P. glauca (white spruce), due to higher diversity and frequencies of rare alleles in Engelmann. Relative to parental species, the proportion of alleles predicted to be deleterious was intermediate in hybrids, and the proportion of loci homozygous for predicted deleterious alleles was lowest.

CONCLUSION

Given that most deleterious alleles are recessive, this suggests that mutation load is reduced in hybrids due to complementation of deleterious alleles. This effect may enhance the fitness of hybrids.

Contributions of Zea mays subspecies mexicana haplotypes to modern maize

Maize was domesticated from lowland teosinte (Zea mays ssp. parviglumis), but the contribution of highland teosinte (Zea mays ssp. mexicana, hereafter mexicana) to modern maize is not clear. Here, two genomes for Mo17 (a modern maize inbred) and mexicana are assembled using a meta-assembly strategy after sequencing of 10 lines derived from a maize-teosinte cross. Comparative analyses reveal a high level of diversity between Mo17, B73, and mexicana, including three Mb-size structural rearrangements. The maize spontaneous mutation rate is estimated to be 2.17 × 10^-8 ~3.87 × 10^-8 per site per generation with a nonrandom distribution across the genome. A higher deleterious mutation rate is observed in the pericentromeric regions, and might be caused by differences in recombination frequency. Over 10% of the maize genome shows evidence of introgression from the mexicana genome, suggesting that mexicana contributed to maize adaptation and improvement. Our data offer a rich resource for constructing the pan-genome of Zea mays and genetic improvement of modern maize varieties.